Look No Deeper: Recognizing Places from Opposing Viewpoints under Varying Scene Appearance using Single-View Depth Estimation

by   Sourav Garg, et al.

Visual place recognition (VPR) - the act of recognizing a familiar visual place - becomes difficult when there is extreme environmental appearance change or viewpoint change. Particularly challenging is the scenario where both phenomena occur simultaneously, such as when returning for the first time along a road at night that was previously traversed during the day in the opposite direction. While such problems can be solved with panoramic sensors, humans solve this problem regularly with limited field of view vision and without needing to constantly turn around. In this paper, we present a new depth- and temporal-aware visual place recognition system that solves the opposing viewpoint, extreme appearance-change visual place recognition problem. Our system performs sequence-to-single matching by extracting depth-filtered keypoints using a state-of-the-art depth estimation pipeline, constructing a keypoint sequence over multiple frames from the reference dataset, and comparing those keypoints to those in a single query image. We evaluate the system on a challenging benchmark dataset and show that it consistently outperforms state-of-the-art techniques. We also develop a range of diagnostic simulation experiments that characterize the contribution of depth-filtered keypoint sequences with respect to key domain parameters including degree of appearance change and camera motion.


page 1

page 3

page 4

page 6


Don't Look Back: Robustifying Place Categorization for Viewpoint- and Condition-Invariant Place Recognition

When a human drives a car along a road for the first time, they later re...

LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics

Human visual scene understanding is so remarkable that we are able to re...

ConvSequential-SLAM: A Sequence-based, Training-less Visual Place Recognition Technique for Changing Environments

Visual Place Recognition (VPR) is the ability to correctly recall a prev...

RoRD: Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching

The use of local detectors and descriptors in typical computer vision pi...

VPR-Bench: An Open-Source Visual Place Recognition Evaluation Framework with Quantifiable Viewpoint and Appearance Change

Visual Place Recognition (VPR) is the process of recognising a previousl...

Connecting Visual Experiences using Max-flow Network with Application to Visual Localization

We are motivated by the fact that multiple representations of the enviro...

Condition-Invariant Multi-View Place Recognition

Visual place recognition is particularly challenging when places suffer ...

Please sign up or login with your details

Forgot password? Click here to reset